SQL Query Design Patterns and Best Practices: A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns
Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine query design and performance using query plans and indexe...
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham ; Mumbai
Packt Publishing
2023
|
| Ausgabe: | 1st edition |
| Schlagworte: | |
| Online-Zugang: | FHD01 |
| Zusammenfassung: | Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine query design and performance using query plans and indexes Solve business problems using advanced techniques such as common table expressions and window functions Use SQL in modern data platform solutions with JSON and Jupyter notebooks Book Description SQL has been the de facto standard when interacting with databases for decades and shows no signs of going away. Through the years, report developers or data wranglers have had to learn SQL on the fly to meet the business needs, so if you are someone who needs to write queries, SQL Query Design and Pattern Best Practices is for you. This book will guide you through making efficient SQL queries by reducing set sizes for effective results. |
| Beschreibung: | 1 Online-Ressource (xix, 249 Seiten) |
| ISBN: | 9781837630080 |
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| 245 | 1 | 0 | |a SQL Query Design Patterns and Best Practices |b A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns |c Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang |
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| 505 | 8 | |a Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Refining Your Queries to Get the Results You Need -- Chapter 1 -- Reducing Rows and Columns in Your Result Sets -- Technical requirements -- Identifying data to remove from the dataset -- Reducing the amount of data -- Understanding the value of creating views versus removing data -- Exploring the impact of row and column reductions on aggregations -- Summary -- Chapter 2 -- Efficiently Aggregating Data -- Technical requirements -- Identifying data to be aggregated | |
| 505 | 8 | |a Determining when data should be aggregated -- The AVG() function -- The SUM() function -- The COUNT() function -- The MAX() function -- The MIN() Function -- Improving performance when aggregating data -- Summary -- Chapter 3 -- Formatting Your Results for Easier Consumption -- Technical requirements -- Using the FORMAT() function -- Format() with culture -- Format() with custom formatting strings -- Formatting dates and numbers with functions -- Formatting dates and numbers with CONVERT() and CAST() -- Formatting numbers with ROUND() and CEILING() -- Comparing FORMAT(), CONVERT(), and CAST() | |
| 505 | 8 | |a Alias columns with meaningful names -- Summary -- Chapter 4 -- Manipulating Data Results Using Conditional SQL -- Technical requirements -- Using the CASE statement -- Using a simple CASE expression in a SELECT statement -- Using a searched CASE expression in a SELECT statement -- Using CASE in an ORDER BY statement -- Using CASE in an UPDATE statement -- Using CASE in a HAVING statement -- Using the COALESCE() expression -- How to use COALESCE() -- Comparing COALESCE() and CASE() -- Using ISNULL() function -- How to use ISNULL() -- Comparing ISNULL() and COALESCE() -- Summary | |
| 505 | 8 | |a Part 2: Solving Complex Business and Data Problems in Your Queries -- Chapter 5 -- Using Common Table Expressions -- Technical requirements -- Creating CTEs -- Set theory for queries -- Creating a more complex CTE -- Creating a recursive CTE -- Creating the hierarchical data -- Creating the recursive CTE -- Recursive alternative -- Summary -- Chapter 6 -- Analyze Your Data Using Window Functions -- Technical requirements -- Understanding window functions -- Using a window function in a query -- Adding a partition to the results -- Window functions with frames -- Scenarios and business problems | |
| 505 | 8 | |a Days between orders -- Finding a pattern -- Finding first N records of every group -- Running totals -- First and last record in the partition -- Year-over-year growth -- Chapter 7 -- Reshaping Data with Advanced Techniques -- Technical requirements -- Working with the PIVOT operator -- Using PIVOT dynamically -- Working with the UNPIVOT operator -- Understanding hierarchical data -- Summary -- Chapter 8 -- Impact of SQL Server Security on Query Results -- Technical requirements -- Why is data missing from my result set? -- Understanding SQL Server security -- Validating security settings | |
| 520 | |a Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine query design and performance using query plans and indexes Solve business problems using advanced techniques such as common table expressions and window functions Use SQL in modern data platform solutions with JSON and Jupyter notebooks Book Description SQL has been the de facto standard when interacting with databases for decades and shows no signs of going away. Through the years, report developers or data wranglers have had to learn SQL on the fly to meet the business needs, so if you are someone who needs to write queries, SQL Query Design and Pattern Best Practices is for you. This book will guide you through making efficient SQL queries by reducing set sizes for effective results. | ||
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| author | Hughes, Steve Neer, Dennis Singh, Ram Babu Mala, Shabbir H. Andrews, Leslie Zhang, Chi |
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| contents | Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Refining Your Queries to Get the Results You Need -- Chapter 1 -- Reducing Rows and Columns in Your Result Sets -- Technical requirements -- Identifying data to remove from the dataset -- Reducing the amount of data -- Understanding the value of creating views versus removing data -- Exploring the impact of row and column reductions on aggregations -- Summary -- Chapter 2 -- Efficiently Aggregating Data -- Technical requirements -- Identifying data to be aggregated Determining when data should be aggregated -- The AVG() function -- The SUM() function -- The COUNT() function -- The MAX() function -- The MIN() Function -- Improving performance when aggregating data -- Summary -- Chapter 3 -- Formatting Your Results for Easier Consumption -- Technical requirements -- Using the FORMAT() function -- Format() with culture -- Format() with custom formatting strings -- Formatting dates and numbers with functions -- Formatting dates and numbers with CONVERT() and CAST() -- Formatting numbers with ROUND() and CEILING() -- Comparing FORMAT(), CONVERT(), and CAST() Alias columns with meaningful names -- Summary -- Chapter 4 -- Manipulating Data Results Using Conditional SQL -- Technical requirements -- Using the CASE statement -- Using a simple CASE expression in a SELECT statement -- Using a searched CASE expression in a SELECT statement -- Using CASE in an ORDER BY statement -- Using CASE in an UPDATE statement -- Using CASE in a HAVING statement -- Using the COALESCE() expression -- How to use COALESCE() -- Comparing COALESCE() and CASE() -- Using ISNULL() function -- How to use ISNULL() -- Comparing ISNULL() and COALESCE() -- Summary Part 2: Solving Complex Business and Data Problems in Your Queries -- Chapter 5 -- Using Common Table Expressions -- Technical requirements -- Creating CTEs -- Set theory for queries -- Creating a more complex CTE -- Creating a recursive CTE -- Creating the hierarchical data -- Creating the recursive CTE -- Recursive alternative -- Summary -- Chapter 6 -- Analyze Your Data Using Window Functions -- Technical requirements -- Understanding window functions -- Using a window function in a query -- Adding a partition to the results -- Window functions with frames -- Scenarios and business problems Days between orders -- Finding a pattern -- Finding first N records of every group -- Running totals -- First and last record in the partition -- Year-over-year growth -- Chapter 7 -- Reshaping Data with Advanced Techniques -- Technical requirements -- Working with the PIVOT operator -- Using PIVOT dynamically -- Working with the UNPIVOT operator -- Understanding hierarchical data -- Summary -- Chapter 8 -- Impact of SQL Server Security on Query Results -- Technical requirements -- Why is data missing from my result set? -- Understanding SQL Server security -- Validating security settings |
| ctrlnum | (OCoLC)1401200032 (DE-599)BVBBV049317005 |
| edition | 1st edition |
| format | Electronic eBook |
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| id | DE-604.BV049317005 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T22:42:22Z |
| indexdate | 2024-07-10T10:01:21Z |
| institution | BVB |
| isbn | 9781837630080 |
| language | English |
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| oclc_num | 1401200032 |
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| owner_facet | DE-1050 |
| physical | 1 Online-Ressource (xix, 249 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE FHD01_PQE_Kauf |
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| spelling | Hughes, Steve Verfasser aut SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang 1st edition Birmingham ; Mumbai Packt Publishing 2023 1 Online-Ressource (xix, 249 Seiten) txt rdacontent c rdamedia cr rdacarrier Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Refining Your Queries to Get the Results You Need -- Chapter 1 -- Reducing Rows and Columns in Your Result Sets -- Technical requirements -- Identifying data to remove from the dataset -- Reducing the amount of data -- Understanding the value of creating views versus removing data -- Exploring the impact of row and column reductions on aggregations -- Summary -- Chapter 2 -- Efficiently Aggregating Data -- Technical requirements -- Identifying data to be aggregated Determining when data should be aggregated -- The AVG() function -- The SUM() function -- The COUNT() function -- The MAX() function -- The MIN() Function -- Improving performance when aggregating data -- Summary -- Chapter 3 -- Formatting Your Results for Easier Consumption -- Technical requirements -- Using the FORMAT() function -- Format() with culture -- Format() with custom formatting strings -- Formatting dates and numbers with functions -- Formatting dates and numbers with CONVERT() and CAST() -- Formatting numbers with ROUND() and CEILING() -- Comparing FORMAT(), CONVERT(), and CAST() Alias columns with meaningful names -- Summary -- Chapter 4 -- Manipulating Data Results Using Conditional SQL -- Technical requirements -- Using the CASE statement -- Using a simple CASE expression in a SELECT statement -- Using a searched CASE expression in a SELECT statement -- Using CASE in an ORDER BY statement -- Using CASE in an UPDATE statement -- Using CASE in a HAVING statement -- Using the COALESCE() expression -- How to use COALESCE() -- Comparing COALESCE() and CASE() -- Using ISNULL() function -- How to use ISNULL() -- Comparing ISNULL() and COALESCE() -- Summary Part 2: Solving Complex Business and Data Problems in Your Queries -- Chapter 5 -- Using Common Table Expressions -- Technical requirements -- Creating CTEs -- Set theory for queries -- Creating a more complex CTE -- Creating a recursive CTE -- Creating the hierarchical data -- Creating the recursive CTE -- Recursive alternative -- Summary -- Chapter 6 -- Analyze Your Data Using Window Functions -- Technical requirements -- Understanding window functions -- Using a window function in a query -- Adding a partition to the results -- Window functions with frames -- Scenarios and business problems Days between orders -- Finding a pattern -- Finding first N records of every group -- Running totals -- First and last record in the partition -- Year-over-year growth -- Chapter 7 -- Reshaping Data with Advanced Techniques -- Technical requirements -- Working with the PIVOT operator -- Using PIVOT dynamically -- Working with the UNPIVOT operator -- Understanding hierarchical data -- Summary -- Chapter 8 -- Impact of SQL Server Security on Query Results -- Technical requirements -- Why is data missing from my result set? -- Understanding SQL Server security -- Validating security settings Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine query design and performance using query plans and indexes Solve business problems using advanced techniques such as common table expressions and window functions Use SQL in modern data platform solutions with JSON and Jupyter notebooks Book Description SQL has been the de facto standard when interacting with databases for decades and shows no signs of going away. Through the years, report developers or data wranglers have had to learn SQL on the fly to meet the business needs, so if you are someone who needs to write queries, SQL Query Design and Pattern Best Practices is for you. This book will guide you through making efficient SQL queries by reducing set sizes for effective results. SQL server SQL server fast Database management Client/server computing SQL (Computer program language) Client/server computing fast Database management fast SQL (Computer program language) fast Neer, Dennis Verfasser aut Singh, Ram Babu Verfasser aut Mala, Shabbir H. Verfasser aut Andrews, Leslie Verfasser aut Zhang, Chi Verfasser aut Erscheint auch als Druck-Ausgabe 978-1-83763-328-9 |
| spellingShingle | Hughes, Steve Neer, Dennis Singh, Ram Babu Mala, Shabbir H. Andrews, Leslie Zhang, Chi SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Refining Your Queries to Get the Results You Need -- Chapter 1 -- Reducing Rows and Columns in Your Result Sets -- Technical requirements -- Identifying data to remove from the dataset -- Reducing the amount of data -- Understanding the value of creating views versus removing data -- Exploring the impact of row and column reductions on aggregations -- Summary -- Chapter 2 -- Efficiently Aggregating Data -- Technical requirements -- Identifying data to be aggregated Determining when data should be aggregated -- The AVG() function -- The SUM() function -- The COUNT() function -- The MAX() function -- The MIN() Function -- Improving performance when aggregating data -- Summary -- Chapter 3 -- Formatting Your Results for Easier Consumption -- Technical requirements -- Using the FORMAT() function -- Format() with culture -- Format() with custom formatting strings -- Formatting dates and numbers with functions -- Formatting dates and numbers with CONVERT() and CAST() -- Formatting numbers with ROUND() and CEILING() -- Comparing FORMAT(), CONVERT(), and CAST() Alias columns with meaningful names -- Summary -- Chapter 4 -- Manipulating Data Results Using Conditional SQL -- Technical requirements -- Using the CASE statement -- Using a simple CASE expression in a SELECT statement -- Using a searched CASE expression in a SELECT statement -- Using CASE in an ORDER BY statement -- Using CASE in an UPDATE statement -- Using CASE in a HAVING statement -- Using the COALESCE() expression -- How to use COALESCE() -- Comparing COALESCE() and CASE() -- Using ISNULL() function -- How to use ISNULL() -- Comparing ISNULL() and COALESCE() -- Summary Part 2: Solving Complex Business and Data Problems in Your Queries -- Chapter 5 -- Using Common Table Expressions -- Technical requirements -- Creating CTEs -- Set theory for queries -- Creating a more complex CTE -- Creating a recursive CTE -- Creating the hierarchical data -- Creating the recursive CTE -- Recursive alternative -- Summary -- Chapter 6 -- Analyze Your Data Using Window Functions -- Technical requirements -- Understanding window functions -- Using a window function in a query -- Adding a partition to the results -- Window functions with frames -- Scenarios and business problems Days between orders -- Finding a pattern -- Finding first N records of every group -- Running totals -- First and last record in the partition -- Year-over-year growth -- Chapter 7 -- Reshaping Data with Advanced Techniques -- Technical requirements -- Working with the PIVOT operator -- Using PIVOT dynamically -- Working with the UNPIVOT operator -- Understanding hierarchical data -- Summary -- Chapter 8 -- Impact of SQL Server Security on Query Results -- Technical requirements -- Why is data missing from my result set? -- Understanding SQL Server security -- Validating security settings SQL server SQL server fast Database management Client/server computing SQL (Computer program language) Client/server computing fast Database management fast SQL (Computer program language) fast |
| title | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns |
| title_auth | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns |
| title_exact_search | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns |
| title_exact_search_txtP | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns |
| title_full | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang |
| title_fullStr | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang |
| title_full_unstemmed | SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang |
| title_short | SQL Query Design Patterns and Best Practices |
| title_sort | sql query design patterns and best practices a practical guide to writing readable and maintainable sql queries using its design patterns |
| title_sub | A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns |
| topic | SQL server SQL server fast Database management Client/server computing SQL (Computer program language) Client/server computing fast Database management fast SQL (Computer program language) fast |
| topic_facet | SQL server Database management Client/server computing SQL (Computer program language) |
| work_keys_str_mv | AT hughessteve sqlquerydesignpatternsandbestpracticesapracticalguidetowritingreadableandmaintainablesqlqueriesusingitsdesignpatterns AT neerdennis sqlquerydesignpatternsandbestpracticesapracticalguidetowritingreadableandmaintainablesqlqueriesusingitsdesignpatterns AT singhrambabu sqlquerydesignpatternsandbestpracticesapracticalguidetowritingreadableandmaintainablesqlqueriesusingitsdesignpatterns AT malashabbirh sqlquerydesignpatternsandbestpracticesapracticalguidetowritingreadableandmaintainablesqlqueriesusingitsdesignpatterns AT andrewsleslie sqlquerydesignpatternsandbestpracticesapracticalguidetowritingreadableandmaintainablesqlqueriesusingitsdesignpatterns AT zhangchi sqlquerydesignpatternsandbestpracticesapracticalguidetowritingreadableandmaintainablesqlqueriesusingitsdesignpatterns |